- Exam Code: A00-402
- Exam Name: SAS Viya 3.5 Supervised Machine Learning Pipelines
- Certification Provider: SASInstitute
- Corresponding Certification:SASInstitute Certification
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SASInstitute A00-402 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Overview of Supervised Machine Learning | 10-15% | - Prediction types and modeling goals - Basic concepts and terminology - Model overfitting, underfitting, and generalization |
| Topic 2: Model Deployment | 5-10% | - Model scoring and operationalization - Registering and publishing models - Exporting score code |
| Topic 3: Building Predictive Models | 25-30% | - Neural networks and deep learning basics - Regularization and optimization methods - Using appropriate modeling nodes - Decision trees and tree ensembles - Regression models (linear, logistic) |
| Topic 4: Creating and Managing Pipelines | 15-20% | - Configuring and connecting nodes - Building pipelines in Model Studio - Using pipeline templates and automation - Managing pipeline flow and execution |
| Topic 5: Model Assessment and Comparison | 15-20% | - Classification metrics: accuracy, precision, recall, F1, AUC - Comparing models and selecting best performer - Profit/loss analysis and cutoff adjustment - Interpreting model results and diagnostics - Regression metrics: RMSE, R-squared, MAE |
| Topic 6: Data Preparation and Exploration | 20-25% | - Partitioning data into training, validation, and test sets - Loading and accessing data sources - Variable selection and reduction - Feature engineering and transformation - Data profiling and exploration - Handling missing values and outliers |
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